CN104599427A - Intelligent image type fire alarming system for highway tunnel - Google Patents
Intelligent image type fire alarming system for highway tunnel Download PDFInfo
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- CN104599427A CN104599427A CN201410834924.1A CN201410834924A CN104599427A CN 104599427 A CN104599427 A CN 104599427A CN 201410834924 A CN201410834924 A CN 201410834924A CN 104599427 A CN104599427 A CN 104599427A
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- 238000012544 monitoring process Methods 0.000 claims abstract description 29
- 239000000779 smoke Substances 0.000 claims abstract description 19
- 238000006243 chemical reaction Methods 0.000 claims description 21
- 238000001514 detection method Methods 0.000 claims description 17
- 238000013528 artificial neural network Methods 0.000 claims description 14
- 238000000605 extraction Methods 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 11
- 238000007781 pre-processing Methods 0.000 claims description 9
- 230000005855 radiation Effects 0.000 claims description 7
- 239000000284 extract Substances 0.000 claims description 5
- 230000008859 change Effects 0.000 claims description 4
- 230000002708 enhancing effect Effects 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract 1
- 238000012549 training Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000003062 neural network model Methods 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000011478 gradient descent method Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000003909 pattern recognition Methods 0.000 description 2
- 238000004321 preservation Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
- 239000000443 aerosol Substances 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 238000004079 fireproofing Methods 0.000 description 1
- 239000003546 flue gas Substances 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000009499 grossing Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000005693 optoelectronics Effects 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 230000007096 poisonous effect Effects 0.000 description 1
- 230000000644 propagated effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000003595 spectral effect Effects 0.000 description 1
- 230000007480 spreading Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- Fire-Detection Mechanisms (AREA)
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- Fire Alarms (AREA)
Abstract
The invention relates to an intelligent image type fire alarming system for a highway tunnel. The fire alarming system comprises a camera for acquiring field data; the camera is connected with the input end of a video image acquiring and transmission module, and two output ends of the camera are respectively connected with a video monitoring module and an image fire detector; the image fire detector is respectively connected with a fire alarm controller and an image fire alarming management module; the image fire alarming management module is used for respectively receiving video monitoring information from the video monitoring module, and fire information from the image fire detector; the image fire alarm management module is connected with a database; the fire alarm connector is connected with the image fire detector; the database is arranged in a computer. With the adoption of the fire alarm system, the smoke detecting function, flame detecting function and the video monitoring function can be carried out synchronously, thus the fire can be accurately determined, an alarm signal can be sent, and as a result, the report error rate can be greatly reduced, and the interference resistance of the alarming system can be improved.
Description
Technical field
The present invention relates to technical field of fire detection, specifically, relate to a kind of intelligent image type fire alarm system for freeway tunnel.
Background technology
Along with the development that China's reform and opening-up is goed deep into further and economic construction is rapid, all trades and professions all achieve very large achievement.Particularly in the last few years, building industry is very prosperous, and various buildings rises abruptly in rapidly China's the earth as emerged rapidly in large numbersBamboo shoots after a spring rain.Wherein the quantity of freeway tunnel is in continuous increase, but often the height of a house is high, span is closed greatly, relatively, escape and rescue is more difficult in freeway tunnel inside, this type of building is once catch fire, fire spreading is rapid, generation flue gas toxity is large, evacuating personnel is difficult and fire attack is difficult, often easily cause very large economic loss and severe social influence, so tunnel fire proofing is a very important job, its objective is that the fire that occurred is eliminated in rudiment or development is early stage, loss is dropped to minimum.The selection of detector for fire alarm system must be accomplished reliably, advanced and there is high sensitivity and rate of false alarm is extremely low, can gapless, whenever and wherever possible, when unmanned the intervention, to tunnel space automatic fire detection-alarm.
Summary of the invention
The object of this invention is to provide a kind of intelligent fire detection alarm system that can be used in vcehicular tunnel, the present invention is according to the optical characteristics of video, smoke detection, flame detecting, video monitoring three kinds of functions can be realized simultaneously, and can determine whether send fire alarm signal according to monitored data, integrated level is high, is confirming burning things which may cause a fire disaster and is realizing the time greatly can saving links in emergency reaction process.
In order to reach foregoing invention object, technical scheme provided by the invention is as follows:
For an intelligent image type fire alarm system for vcehicular tunnel, it is characterized in that, this fire alarm system includes:
Camera, this camera is used for the field data in Real-time Collection vcehicular tunnel, and field data is transferred to video image acquisition and transport module;
Video image acquisition and transport module, camera described in its input end connects, two output terminals connect video monitoring module and image-type fire detector respectively, include sensor unit, photoelectric conversion unit and AD conversion unit in video image acquisition and transport module;
Image-type fire detector, this image-type fire detector connects fire alarm control unit and image fire alarming and managing module respectively, and this image-type fire detector carries out smog image procossing and flame Image Processing to realize smoke detection and flame detecting simultaneously;
Video monitoring module, the output terminal connection layout of this video monitoring module is as fire alarm administration module and export real-time video monitoring information;
Image fire alarming and managing module, it receives the video monitoring information from video monitoring module and the fire information from image-type fire detector respectively, is shown in computing machine, this image fire alarming and managing model calling database;
Fire alarm control unit, this fire alarm control unit connects image-type fire detector;
Database, this database is located in computing machine, for the preservation of video and fire alarm information, so that the inquiry later to historical information.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described video image acquisition and transport module are by gathering the radiation signal of scene of fire flame and smog as the imageing sensor in sensor unit, radiation signal is converted to analog video signal by photoelectric conversion unit, and AD conversion unit is by analog video signal conversion also boil down to digital image sequence.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described image-type fire detector is provided with smoke detection unit, flame detecting unit, image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, data in smoke detection unit and flame detecting unit respectively through image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, the export structure interlock image fire alarming and managing module of fire judgement unit and fire alarm control unit.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described image pre-processing unit comprises filtering process, edge enhancing, binaryzation, segmentation and registration process, remove interference, noise level difference, original image is become and is suitable for the form that computing machine carries out feature extraction.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described image characteristics extraction unit comprises smoke characteristics and extracts and flame characteristic extraction, smoke characteristics includes spatial resolution, frequecy characteristic and directivity characteristics, and flame characteristic includes flame color, flicker frequency and brightness change.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described Intelligent Recognition unit adopts artificial neural network, classifies and identification to image information, and image information classification includes fire condition, alarm condition and normal condition.
Be used in the intelligent image type fire alarm system of vcehicular tunnel in the present invention, described fire judgement unit according to image information classification and preset standard comparison to be confirmed whether breaking out of fire, report to the police as breaking out of fire then starts fire alarm control unit, and fire information and video information are presented in image fire alarming and managing module.
Based on technique scheme, of the present invention for the intelligent image type fire alarm system of vcehicular tunnel in there is following technological merit:
1. the feature that intelligent image type fire alarm system of the present invention is maximum is that it can carry out smoke detection, flame detecting simultaneously, and integrated level is high, has saved system cost greatly, has reduced the complicacy of system installation and maintenance.
2. intelligent image type fire alarm system of the present invention adopts advanced photoelectric imaging technology, computer image processing technology, there is contactless detection, high intelligence, feature sensitive by force and by the restriction of spatial altitude, gas velocity, the environmental baseline such as explosive, poisonous, can detect early stage flame and the smog of generation in time, be the effective means that vcehicular tunnel carries out detection.
3. intelligent image type fire alarm system of the present invention adopts visual warning, realizes detection and video monitoring dual-use function.When fire occurs, Surveillance center ejects live real-time video picture immediately, and identify fire particular location, confirming for operator on duty, substantially reduce the time determined burning things which may cause a fire disaster He realize emergency reaction process, providing " time " guarantee for putting out burning things which may cause a fire disaster redemption lives and properties in time fast.
4. intelligent image type fire alarm system investigative range of the present invention is large, and distance, structure simply construct wiring conveniently, and easy-to-use handy compatibility is strong.
Accompanying drawing explanation
Fig. 1 is the system architecture schematic diagram of intelligent image type fire alarm system of the present invention.
Fig. 2 is the flow chart of data processing schematic diagram of intelligent image type fire alarm system of the present invention.
Fig. 3 is video image acquisition of the present invention and transport module flow chart of data processing schematic diagram.
Embodiment
We are described in further detail the intelligent image type fire alarm system for vcehicular tunnel of the present invention with specific embodiment by reference to the accompanying drawings below; understand its principle of work and embody rule in the hope of more clear, but can not limit the scope of the invention with this.
As shown in Figure 1, Fig. 1 is the intelligent image type fire alarm system structural representation for vcehicular tunnel of the present invention, and intelligent image type fire alarm system of the present invention is mainly made up of camera 1, video image acquisition and transport module 2, video monitoring module 3, image-type fire detector 4, image fire alarming and managing module 5, fire alarm control unit 6 and database 7.
Wherein, camera 1 is installed in vcehicular tunnel, for the field data in Real-time Collection vcehicular tunnel, and field data is transferred to video image acquisition and transport module 2.The camera 1 described in input end connection of video image acquisition and transport module 2, two output terminals of video image acquisition and transport module 2 connect video monitoring module 3 and image-type fire detector 4 respectively, in video image acquisition and transport module 2, include sensor unit, photoelectric conversion unit and AD conversion unit.
Above-mentioned image-type fire detector 4 connects fire alarm control unit 6 and image fire alarming and managing module 5 respectively, and this image-type fire detector 4 carries out smog image procossing and flame Image Processing to realize smoke detection and flame detecting simultaneously.The output terminal connection layout of video monitoring module 3 is as fire alarm administration module 5 and export real-time video monitoring information, image fire alarming and managing module 5 receives from the video monitoring information of video monitoring module 3 and the fire information from image-type fire detector 4 respectively, this image fire alarming and managing module 5 connection data storehouse 7, described database 7 is located in computing machine, this database 7 is connected with described image fire alarming and managing module 5, for receiving the preservation of its video transmitted and fire alarm information, so that the inquiry later to historical information.Fire alarm control unit 6 connects image-type fire detector 4.
The randomness occurred due to fire is strong, the place of breaking out of fire cannot be estimated, camera 1 is carried out when installing in vcehicular tunnel, according to size, the structure in space, consider the density of camera 1 installation, position, the visual angle of monitoring will avoid monitoring site occur dead angle and fail to report, and considers its sharpness, signal to noise ratio (S/N ratio), outer synchronous and spectral response characteristic during the selection of camera.
Fig. 2 is the flow chart of data processing schematic diagram of intelligent image type fire alarm system of the present invention.First on-the-spot video monitoring image is obtained by camera 1, then after video image acquisition and transport module 2 process, digital image sequence is obtained, namely the image information that image-type fire detector 4 receives video image acquisition and transport module 2 carries out pre-service to it, and the visual signature information of proposition smog, flame image carries out intellectual analysis and identification.
Can condition of a fire point if found after image recognition, to be linked image fire alarming and managing module 5, fire alarm control unit 6, by image fire alarming and managing module 5 by fire parameter information and video monitoring informations such as the spatial positional informations of fire origination point, be shown on computing machine, and carry out burning things which may cause a fire disaster location, automatic control shower nozzle is put out a fire in time, exactly in real time, starts sound and light alarm simultaneously and warning message is notified related personnel with the form of note by fire alarm control unit 6.
Wherein, video image acquisition and transport module 2 comprise 3 big units as shown in Figure 3: image sensor cell, photoelectric conversion unit, A/D converting unit.First it pass through the radiation signal of image sensor cell Real-time Collection scene of fire flame and smog, becoming simulating signal vision signal through opto-electronic conversion, finally after A/D conversion also compressed encoding, forming digital image sequence.
Described video image acquisition and transport module are by gathering the radiation signal of scene of fire flame and smog as the imageing sensor in sensor unit, radiation signal is converted to analog video signal by photoelectric conversion unit, and AD conversion unit is by analog video signal conversion also boil down to digital image sequence.
Of the present invention in the intelligent image type fire alarm system of vcehicular tunnel, described image-type fire detector 4 reality is image processing process, and it can carry out smog image procossing, flame Image Processing simultaneously, realizes smoke detection and flame detecting.Image-type fire detector is provided with smoke detection unit, flame detecting unit, image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, data in smoke detection unit and flame detecting unit respectively through image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, the export structure interlock image fire alarming and managing module of fire judgement unit and fire alarm control unit.Before processing image, need pre-service to comprise filtering process, edge enhancing, binaryzation, segmentation and registration etc., object eliminates certain interference, be conducive to the efficiency improving image processing and analyzing, then the image processing techniques based on Wavelet transformation is adopted to carry out characteristics of image proposition, then adopt the method for artificial neural network to carry out pattern recognition classifier according to characteristics of image, then determine whether breaking out of fire by fire judgement unit.
The concrete steps of above-mentioned image-type fire detector 4 are as follows:
Data pre-processing unit: described image-type fire detector is first to the smog received with Digital Flame Image ordered series of numbers is smoothing and Edge contrast, eliminate or noise decrease impact as far as possible, then binary conversion treatment is carried out to digital picture, extract the target image of reflection integral image and local feature, then adopt image subtraction computing to remove the background of image.
Image characteristics extraction unit: image-type fire detector 4 utilizes wavelet transformation by target image by after flexible and translation, extract respectively and can represent and distinguish the smog of this target image, the various variation characteristic information of flame, specifically comprise smoke characteristics to extract and flame characteristic extraction, smoke characteristics includes spatial resolution, frequecy characteristic and directivity characteristics, and flame characteristic includes flame color, flicker frequency and brightness change.
Intelligent Recognition unit: Intelligent Recognition unit adopts artificial neural network to classify and identification to image information, image information classification includes fire condition, alarm condition and normal condition, BP network model in artificial neural network is specifically adopted to carry out pattern recognition classifier, its course of work can be divided into study and two stages of classification, the former is the sample data according to image, carries out self study by network itself according to certain rule; Latter utilizes the structure of study to classify to entire image.
Fire judgement unit: described fire judgement unit according to image information classification and preset standard comparison to be confirmed whether breaking out of fire, report to the police as breaking out of fire then starts fire alarm control unit, and fire information and video information are presented in image fire alarming and managing module.In Intelligent Recognition unit, its operation result is transferred to fire judgement unit by BP neural network model, judges fire condition by it according to 0 (k).
In Intelligent Recognition unit, BP neural network learning process is as follows:
A. first training sample obtains, and M the characteristic parameter according to extracting carries out sample classification to target image, then from M group target image, respectively randomly draws one, forms a M dimensional feature vector, extracts and repeatedly forms training sample set;
B. then BP neural network model is built, make M characteristic parameter of the corresponding target image of the input node of BP neural network, for the node i=M of BP neural network input layer, make corresponding fire identification result 0 (k) of the output node of BP neural network, the value of 0 (k) is 0 (k)
[0,1], wherein, 0 (k)
[0.75,1] is " fire condition ", 0 (k)
[0.25,0.75] is " alarm condition ", 0 (k)
[0,0.25] is " normal condition ", the nodes k=1 of corresponding BP neural network output layer; Then the nodes of BP neural network hidden layer is calculated;
C. the training of neural network, what neural network adopted is three etale topology structures, i.e. input layer, hidden layer, output layer, and input layer information is determined by the both image change characteristics of the fire hazard aerosol fog extracted, flame.The training flow process of neural network is as follows:
Parameter initialization: the parameters such as the setting of setting input layer maximum iteration time, least error, learning rate, by input layer
with hidden layer
connection weights
, hidden layer
with output layer
connection weights
be initialized as the random number between (-1,1).
Information propagated forward process computation, by training sample
be input to the input layer of BP neural network model, by input
obtain the input value of hidden layer node
, wherein
for input layer
the output valve of node, that is
the input value of node.So hidden layer
output be
; Then pass through
obtain output layer
being input as of node
; Finally obtain output layer
the output of node is
.
Error back-propagating process computation.Suppose that desired output is
, then the average error of output terminal is
, then utilize the weights between gradient descent method modulation hidden layer and output layer
.In like manner, according to the error on hidden layer node, adopt the weights between gradient descent method adjustment input layer and hidden layer
, circulation step 2 and 3, until reach maximum frequency of training or meet least error.
Preserve the weights of each layer, and utilize the parameter succeeded in school to identify new samples.
Intelligent image type fire alarm system of the present invention is mainly used to monitor the flame in vcehicular tunnel and smog, can carry out the Real-Time Monitoring of non-intervention type to fire conditions in tunnel and automatically can determine whether send fire alarm signal according to monitored data.By the present invention, judge fire alarm accurately and reliably and provide alerting signal, reducing rate of false alarm, alarm system for lifting antijamming capability.
Claims (7)
1., for an intelligent image type fire alarm system for vcehicular tunnel, it is characterized in that, this fire alarm system includes:
Camera, this camera is used for the field data in Real-time Collection vcehicular tunnel, and field data is transferred to video image acquisition and transport module;
Video image acquisition and transport module, camera described in its input end connects, two output terminals connect video monitoring module and image-type fire detector respectively, include sensor unit, photoelectric conversion unit and AD conversion unit in video image acquisition and transport module;
Image-type fire detector, this image-type fire detector connects fire alarm control unit and image fire alarming and managing module respectively, and this image-type fire detector carries out smog image procossing and flame Image Processing to realize smoke detection and flame detecting simultaneously;
Video monitoring module, the output terminal connection layout of this video monitoring module is as fire alarm administration module and export real-time video monitoring information;
Image fire alarming and managing module, it receives the video monitoring information from video monitoring module and the fire information from image-type fire detector respectively, this image fire alarming and managing model calling database;
Fire alarm control unit, this fire alarm control unit connects image-type fire detector;
Database, this database is located in computing machine.
2. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 1, it is characterized in that, described video image acquisition and transport module are by gathering the radiation signal of scene of fire flame and smog as the imageing sensor in sensor unit, radiation signal is converted to analog video signal by photoelectric conversion unit, and AD conversion unit is by analog video signal conversion also boil down to digital image sequence.
3. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 1, it is characterized in that, described image-type fire detector is provided with smoke detection unit, flame detecting unit, image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, data in smoke detection unit and flame detecting unit are respectively through image pre-processing unit, image characteristics extraction unit, Intelligent Recognition unit and fire judgement unit, the export structure interlock image fire alarming and managing module of fire judgement unit and fire alarm control unit.
4. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 3, it is characterized in that, described image pre-processing unit comprises filtering process, edge enhancing, binaryzation, segmentation and registration process, remove interference, noise level difference, original image is become and is suitable for the form that computing machine carries out feature extraction.
5. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 3, it is characterized in that, described image characteristics extraction unit comprises smoke characteristics and extracts and flame characteristic extraction, smoke characteristics includes spatial resolution, frequecy characteristic and directivity characteristics, and flame characteristic includes flame color, flicker frequency and brightness change.
6. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 3, it is characterized in that, described Intelligent Recognition unit adopts artificial neural network, classifies and identification to image information, and image information classification includes the non-fire of the first kind and Equations of The Second Kind fire.
7. a kind of intelligent image type fire alarm system for vcehicular tunnel according to claim 3, it is characterized in that, described fire judgement unit according to image information classification and preset standard comparison to be confirmed whether breaking out of fire, report to the police as breaking out of fire then starts fire alarm control unit, and fire information and video information are presented in image fire alarming and managing module.
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